Soft IoT

Gait Analyses. Pressure sensors in the slippers provide data that can be processed to derive the digital representation of the gait of the person.

We find the Soft IoT in the data space. They are entities by themselves, sometimes raw entities, whose value derives from sensors, sometimes they are entities resulting from computation of other data or data entities. In any case, as shown before, they have an identity, area characterised by a set of rules and have properties. They are capable of interacting with their environment and can be more or less sophisticated.

Let’s take a look at a few categories of Soft IoT. Let’s start with SoftBots.

They all have in common a dynamic relation with the ambient. A soft Bot (as an IoT) has its own identity and related to the surrounding ambient by sensing what is going on. Differently from an IoT the definition of surronding ambient comprises whatever is within the reach of a message exchange. There are no geographical proximity limitation. A soft Bot can connect to another soft Bot that can reside in a server on the other side of the world.

The sensing is processed by a more or less sophisticated agent that may have a fixed set of operations or a variable set . Its flexibility a latitude of processing is an indicator, although not the only one, of its smartness. The result of its perception of the ambient results in a set of actions, be it alerts or creation of new soft Bot that can link to other soft IoT, to soft Bots, to IoT to services.

Avatars can be considered as particular type of SoftBots. Today they are seen as impersonators, capturing the characters of a person (a subset of them) and representing that person in certain contexts. Clearly there is no guarantee, in general, that the charaterization is faithful to the original. On the contrary, sometimes people may elect to be impersonated by an avatar that is showing different charcteristics from them, including the morphology (you may want ot be impersonated by a cat).

In the coming years our person will be mirrored by a digital person with a range of degrees of similarity. There have been a number of science fiction novels based on the existance of a digital self that is exaclty replicating the physical self. They all point out some unexpected twist in the concept of “identical”. See Mind’s I for examples.

What used to be science fiction or thought experiment is now getting closer to science and to implementation issues.

We can expect in the coming years to have more and more accurate digital copies of ourselves, whare accurate refers not to an identity, rather to the representation goal associated to the avatar. In other words, I only care that the avatar faithfully represents me in a given situation within well defined boundaries. I am not asking, nor I would want, to have an exact replica of myself.

Another example of a Soft IoT is the representation of gait. Sensors of various types, images captured by a video camer, pressure sensors in a shoe or slipper, accelerator in sneakers can provide data that once aggregated and procesed can create an information on the gait. This is just another information, so why should I call it a Soft IoT? Well one could transform this data into a Soft IoT by a associating rules that prescribe when to generate an alert once a change in gait is detected. This is actually what happens in data associated to slippers provided by MGH to outpatients having suffered from a stroke. The patients have a higher risk of recurrence and doctors have noticed that 24-48 h before a recurrence the gait may become altered. By creating a soft IoT they can monitor the gait and be alerted if something unusual happens.

The changing values associated to the Soft IoT mirroring the patient gait can be related to the ones of other patients and to the actual recurrence of a stroke in some of them, leading ot an improved sensitivity of this Soft IoT.

Recent studies have shown that measuring the changing reflection of an electromagnetic field caused by the breathing and heart beating rate can provide telling signs of a person “mood”. By creating Soft IoT connected to each person it becomes possibile to compare potential mood changes to ambient situation, to the context (a person being alone, or in a cluster of other people…). These Soft IoT can be used as virtual objects representing feelings and can be studied as such.

This example, as well as the previous on gait are also example of the creation of a "digital signature".